SUMMARY. Bicuspid Aortic Valve (BAV) is the most common congenital heart defect in the US and is associated with frequent and premature occurrence of aortic stenosis (AS) and ascending thoracic aortic aneurysm (TAA). It has been estimated that 30-50% of BAV patients will require surgical intervention in their life for valvulopathy, aortopathy or both. While AS is a degenerative process that span over a decade, a dissection or rupture of the aorta has devastating consequences. One of today?s major clinical controversies among cardiologists and cardiac surgeons is the management of BAV patients for the risk of adverse aortic events. According to the the current guidelines, BAV patients are risk-stratified using metric measurements obtained by imaging techniques. Although aortic diameter, expansion rate, and ratio of aortic area/diameter to body weight/surface are the current indications for elective surgical intervention, they are imperfect predictors of aortic dissection and rupture. The lack of correlation between diameter and histologic abnormality in the setting of BAV highlights the inadequacy of diameter alone as a reason for aortic resection. New approaches to study aortic wall homeostasis are clearly needed, and new methodologies to implement imaging techniques based on aortic wall microstructure should be prioritized. In doing so, this application addresses areas that the NIH has identified as important, understudied topics, including the characterization of pre-onset identification and preventive treatment of vascular diseases. Failing to do so, will lead to the continued use of inadequate clinical managements of BAV patients with suboptimal care. This application fills this gap. Our goal is to investigate BAV predisposition to adverse aortic events and to unveil the diagnostic and therapeutic potentials of the AGE/ROS/myocardin axis. Aim 1 will determine BAV predisposition to proximal aortopathies and is association to altered AGE/ROS/myocardin signaling in human VSMCs and aortic wall tissues. BAV patients will be enrolled and risk-stratified according to sRAGE level and analyzed ex vivo for dysfunction of the aortic wall by biomechanical testing. BAV-derived VSMC plasticity will be determined in vitro by dissecting RAGE/ROS/myocardin signaling using novel SOD mimetics (MnTE-2-PyP5+ and MnTnBuOE-2-PyP5+), anti- and pre-miR143, and myocardin siRNA. Endpoints and readouts will include ECM remodeling, VSMC phenotype, proliferation, and apoptosis. Cell- and tissue-derived data will be coupled with circulating markers and imaging analysis for the risk stratification of BAV patients including different BAV anatomical configuration. Notably, we have the ability to test over a thousand non surgical patients. Thus, our data move beyond purely basic science questions and begin to address questions about clinical management based on new risk- stratification tools. Aim 2 will modulate AGE/ROS/myocardin signaling in vivo and determine its impact on aortic wall remodeling in BAV and TAV murine models. AGE/ROS/myocardin axis will be dissected at multiple level in vivo by implementing pharmacological approaches and selected genetic backgrounds. Capitalizing on Myocd conditional (SM-MyHC-CreERT/MyocdF/F), RAGE-/-, and eNOS-/- (selected for BAV presence by echo), we will test the role of Ang II chronic infusion on AV and ascending aortic remodeling modulating miR143 (Pre-miR143 and LNAmiR143) or oxidative stress (Mn-porphyrins). AV function and aortic dilation will be tested echocardiographically; aortic remodeling will be determined by VSMC phenotype and ECM remodeling. Thus, this application has two important outcomes for public health: in the short term, it will provide physicians and scientists a tool (in addition to the current imaging techniques), to identify a patient population at high risk of valve and vascular pathologies. In the long term, it will provide mechanistic information on the cellular and molecular events leading to ascending aortopathies, which will be integral to personalized therapies for high-risk individuals.